This paper presents a search for direct top squark pair production in events with missing transverse momentum plus either a pair of jets consistent with Standard Model Higgs boson decay into b-quarks or a same-flavour opposite-sign dilepton pair with an invariant mass consistent with a Z boson. The analysis is performed using the proton–proton collision data at s=13\documentclass[12pt]{minimal}
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\begin{document}$$^{-1}$$\end{document}. No excess is observed in the data above the Standard Model predictions. The results are interpreted in simplified models featuring direct production of pairs of either the lighter top squark (t~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1$$\end{document}) or the heavier top squark (t~2\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_2$$\end{document}), excluding at 95% confidence level t~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1$$\end{document} and t~2\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_2$$\end{document} masses up to about 1220 and 875 GeV, respectively.
publisher-imprint-nameSpringervolume-issue-count12issue-article-count93issue-toc-levels0issue-pricelist-year2020issue-copyright-holderThe Author(s)issue-copyright-year2020article-contains-esmNoarticle-numbering-styleContentOnlyarticle-registration-date-year2020article-registration-date-month9article-registration-date-day14article-toc-levels0toc-levels0volume-typeRegularjournal-productNonStandardArchiveJournalnumbering-styleContentOnlyarticle-grants-typeOpenChoicemetadata-grantOpenAccessabstract-grantOpenAccessbodypdf-grantOpenAccessbodyhtml-grantOpenAccessbibliography-grantOpenAccessesm-grantOpenAccessonline-firstfalsepdf-file-referenceBodyRef/PDF/10052_2020_Article_8469.pdfpdf-typeTypesettarget-typeOnlinePDFissue-online-date-year2020issue-online-date-month12issue-online-date-day21issue-typeRegulararticle-typeOriginalPaperjournal-subject-primaryPhysicsjournal-subject-secondaryElementary Particles, Quantum Field Theoryjournal-subject-secondaryNuclear Physics, Heavy Ions, Hadronsjournal-subject-secondaryQuantum Field Theories, String Theoryjournal-subject-secondaryMeasurement Science and Instrumentationjournal-subject-secondaryAstronomy, Astrophysics and Cosmologyjournal-subject-secondaryNuclear Energyjournal-subject-collectionPhysics and Astronomyopen-accesstrueIntroduction
Supersymmetry (SUSY) [1–6] is one of the most studied frameworks to extend the Standard Model (SM) beyond the electroweak scale. It predicts new bosonic (fermionic) partners for the known fermions (bosons). Assuming R-parity conservation [7], SUSY particles are produced in pairs and the lightest supersymmetric particle (LSP) is stable, providing a possible dark-matter candidate. The SUSY partners of the Higgs bosons and electroweak gauge bosons mix to form the mass eigenstates known as charginos (χ~k±\documentclass[12pt]{minimal}
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\begin{document}$$m = 1, 2, 3, 4$$\end{document}), where the increasing index denotes increasing mass. The scalar partners of right-handed and left-handed quarks, q~R\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{q}_{1}$$\end{document} defined to be the lighter of the two. To address the SM hierarchy problem [8–11], TeV\documentclass[12pt]{minimal}
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\begin{document}$$\text {TeV}$$\end{document}-scale masses are favoured [12, 13] for the supersymmetric partners of the gluons, and the top squarks [14, 15].
Diagrams for the top squark pair production processes considered in this analysis: a with decays (showing for illustration the case where the two decay differently, although events with the same decays are also considered in the analysis), and bt~2→Zt~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_2 \rightarrow Z \tilde{t}_1 $$\end{document} with decays
Top squark production with SM Higgs (h) or Z bosons in the decay chain can appear either in production of the lighter top squark mass eigenstate (t~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1$$\end{document}) decaying via with , or in production of the heavier top squark mass eigenstate (t~2\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_2 \rightarrow Z \tilde{t}_1 $$\end{document} with , as illustrated in Fig. 1. Unlike other top squark models, these signals can be efficiently distinguished from the SM top quark pair production (tt¯\documentclass[12pt]{minimal}
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\begin{document}$$t\bar{t} $$\end{document}) background by requiring either a same-flavour opposite-sign (SF-OS) lepton pair originating from the Z→ℓ+ℓ-\documentclass[12pt]{minimal}
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\begin{document}$$\ell \equiv e, \mu $$\end{document}) decay or a pair of b-tagged jets originating from the h→bb¯\documentclass[12pt]{minimal}
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\begin{document}$$h\rightarrow b\bar{b} $$\end{document} decay, plus the presence of an additional lepton produced in the decay of the top quarks in the event.
Simplified models [16–18] are used for the analysis optimisation and interpretation of the results. In these models, direct top squark pair production is considered and all SUSY particles are decoupled except for the top squarks and the neutralinos involved in their decay. In all cases the is assumed to be the LSP. Simplified models featuring direct t~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1 $$\end{document} production with and decays via either Higgs () or Z () bosons with different branching ratio values are considered. In these models, the is assumed to be very light and the mass difference to be large enough to allow on-shell Higgs or Z boson decays.
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\begin{document}$$\tilde{t}_2 \rightarrow Z\tilde{t}_1 $$\end{document} decays and are also considered. The mass difference between the t~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1 $$\end{document} and is set to be smaller than the W boson mass, and the four-body decay is assumed to occur, where f and f′\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1$$\end{document} pair production contribution to the selections presented in this paper has been found to be negligible.
This paper presents the results of a search for top squarks in final states with Higgs or Z bosons at s=13\documentclass[12pt]{minimal}
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\begin{document}$$\text {TeV}$$\end{document} using the complete data sample collected with the ATLAS detector [19] in proton–proton (pp) collisions during Run-2 of the LHC (2015–2018), corresponding to 139 fb-1\documentclass[12pt]{minimal}
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\begin{document}$$\hbox {fb}^{-1}$$\end{document}. Searches for top squark production in events involving Higgs or Z bosons have been performed previously by both ATLAS [20, 21] and CMS [22, 23].
ATLAS detector
The ATLAS detector [19, 24] at the LHC is a multipurpose particle detector with a forward–backward symmetric cylindrical geometry and a near 4π\documentclass[12pt]{minimal}
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\begin{document}$$4\pi $$\end{document} coverage in solid angle.1 It consists of an inner tracking detector (ID) surrounded by a thin superconducting solenoid providing a 2 T axial magnetic field, electromagnetic (EM) and hadron calorimeters, and a muon spectrometer (MS). The inner tracking detector covers the pseudorapidity range |η|<2.5\documentclass[12pt]{minimal}
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\begin{document}$$|\eta | = 4.9$$\end{document}. The muon spectrometer surrounds the calorimeters and is based on three large air-core toroidal superconducting magnets with eight coils each. The field integral of the toroids ranges between 2 and 6 T m across most of the detector. The muon spectrometer includes a system of precision tracking chambers and fast detectors for triggering. A two-level trigger system is used to select events [25]. The first-level trigger is implemented in hardware and uses a subset of the detector information to reduce the accepted rate to at most 100 kHz. This is followed by a software-based trigger that reduces the accepted event rate to 1 kHz on average depending on the data-taking conditions.
Simulated signal and background event samples: the corresponding event generator used for the hard-scatter process, the generator used to model the parton showering, the source of the cross-section used for normalisation, the PDF set and the underlying-event tune are shown
The data were collected by the ATLAS detector during the LHC Run-2 (2015–2018) with a peak instantaneous luminosity of L=2.1×1034cm-2s-1\documentclass[12pt]{minimal}
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\begin{document}$$139\hbox { fb}^{-1}$$\end{document}. The uncertainty in the combined 2015–2018 integrated luminosity is 1.7%. It is derived from the calibration of the luminosity scale using x–y beam-separation scans, following a methodology similar to that detailed in Ref. [26], and using the LUCID-2 detector for the baseline luminosity measurements [27].
Monte Carlo (MC) simulated event samples are used to aid the estimation of the background from SM processes and to model the SUSY signal. The choices of MC event generator, parton shower and hadronisation, the cross-section normalisation, the parton distribution function (PDF) set and the set of tuned parameters (tune) for the underlying event of these samples are summarised in Table 1. More details of the event generator configurations can be found in Refs. [28–31]. Cross-sections calculated at next-to-next-to-leading order (NNLO) in quantum chromodynamics (QCD) including resummation of next-to-next-to-leading logarithmic (NNLL) soft-gluon terms were used for top quark production processes. For production of top quark pairs in association with vector or Higgs bosons, cross-sections calculated at next-to-leading order (NLO) were used, and the event generator NLO cross-sections from Sherpa [32] were used when normalising the multi-boson backgrounds. In all MC samples, except those produced by Sherpa, the EvtGen v1.2.0 program [33] was used to model the properties of the bottom and charm hadron decays.
SUSY signal samples were generated with MG5_aMC@NLO 2.6.2 [34] interfaced to Pythia 8.212 [35] for the parton showering (PS) and hadronisation. The matrix element (ME) calculation was performed at tree level and includes the emission of up to two additional partons for all signal samples. MadSpin [55] was used to model the decays. MadSpin emulates kinematic distributions to a good approximation without calculating the full ME. The PDF set used for the generation of the signal samples was NNPDF2.3LO [40] with the A14 [41] set of tuned underlying-event and shower parameters (UE tune). The ME–PS matching was performed with the CKKW-L prescription [56], with a matching scale set to one quarter of the top squark mass. All signal cross-sections were calculated to approximate NNLO in the strong coupling constant, adding the resummation of soft gluon emission at NNLL accuracy (approximate NNLO+NNLL) [36–39]. The nominal cross-section and its uncertainty were derived using the PDF4LHC15_mc PDF set, following the recommendations of Ref. [57].
To simulate the effects of additional pp collisions in the same and nearby bunch crossings (pile-up), additional interactions were generated using the soft QCD processes provided by Pythia 8.186 with the A3 tune [58] and the MSTW2008LO PDF set [59], and overlaid onto each simulated hard-scatter event. The MC samples were reweighted so that the pile-up distribution matches the one observed in the data. The MC samples were processed through an ATLAS detector simulation [60] based on Geant 4 [61] or, in the case of tt¯t\documentclass[12pt]{minimal}
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\begin{document}$$t\bar{t} t$$\end{document} and the SUSY signal samples, a fast simulation using a parameterisation of the calorimeter response and Geant 4 for the other parts of the detector. All MC samples were reconstructed in the same manner as the data.
Event selection
Candidate events are required to have a reconstructed vertex [62] with at least two associated tracks with transverse momentum (pT\documentclass[12pt]{minimal}
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\begin{document}$$|\eta |<2.5$$\end{document} are required to have a significant fraction of their associated tracks compatible with originating from the primary vertex, as defined by the jet vertex tagger [68]. This requirement reduces the fraction of jets from pile-up to 1%, with an efficiency for hard-scatter jets of about 90%. Events are discarded if they contain any jet with pT>20GeV\documentclass[12pt]{minimal}
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\begin{document}$$p_{\text {T}} >20~\hbox {GeV}$$\end{document} not satisfying basic quality selection criteria designed to reject detector noise and non-collision backgrounds [69].
Identification of jets containing b-hadrons (b-tagging) is performed with a multivariate discriminant that makes use of track impact parameters and reconstructed secondary vertices [70, 71]. Jets are considered as b-tagged if they fulfil a requirement corresponding to a 77% average efficiency obtained for jets containing b-hadrons in simulated tt¯\documentclass[12pt]{minimal}
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\begin{document}$$\Delta R= {\text {min}}\{0.4, 0.04 + p_{\text {T}} (\mu )/10\hbox { GeV}\}$$\end{document} of a non-pile-up jet is discarded. In the latter case, if the jet has fewer than three associated tracks, the muon is retained and the jet is discarded instead to avoid inefficiencies for high-energy muons undergoing significant energy loss in the calorimeter. Finally, any electron candidate sharing an ID track with a remaining muon candidate is also removed.
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Signal region SR1Ah\documentclass[12pt]{minimal}
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Comparison of the relative uncertainty for the total background yield in each SR, including the contribution from the different sources of uncertainty. The ‘Detector’ category contains all detector-related systematic uncertainties and is dominated by jet energy scale and resolution, and b-tagging uncertainties
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\begin{document}$$\hbox {SR}_{1\mathrm{B}}^{h}$$\end{document}, for events passing all the SR requirements except those on the variable being plotted (the requirements are indicated by the arrows). The contributions from all SM backgrounds are shown after the background fit described in Sect. 5; the hashed bands represent the total uncertainty. The ‘Higgs’ category contains the contributions from gluon–gluon fusion, vector-boson fusion, Wh, Zh and tt¯h\documentclass[12pt]{minimal}
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\begin{document}$$t\bar{t} t\bar{t} $$\end{document} production. The expected distributions for selected signal models are also shown as dashed lines. The last bin in each figure contains the overflow
Systematic uncertainties
The main sources of systematic uncertainty affecting the analysis SRs are related to the theoretical and modelling uncertainties in the background, the limited number of events in the CRs and MC simulated samples, the uncertainties in the FNP probabilities, as well as the jet energy scale and resolution. The effects of the systematic uncertainties are evaluated for all signal samples and background processes. Since the normalisation of the dominant background processes is extracted in dedicated CRs, the systematic uncertainties only affect the extrapolation to the SRs in these cases. Figure 5 summarises the contributions from the different sources of systematic uncertainty to the total SM background predictions in the signal regions.
The jet energy scale and resolution uncertainties are derived as a function of the pT\documentclass[12pt]{minimal}
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\begin{document}$$\eta $$\end{document} of the jet, as well as of the pile-up conditions and the jet flavour composition (more like a quark or a gluon) of the selected jet sample. They are determined using a combination of data and simulated event samples, through measurements of the jet response asymmetry in dijet, Z+jet and γ+\documentclass[12pt]{minimal}
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\begin{document}$$\gamma +$$\end{document}jet events [67, 84].
Systematic uncertainties in the b-tagging efficiency are estimated by varying the η\documentclass[12pt]{minimal}
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\begin{document}$$p_{\text {T}} $$\end{document}- and flavour-dependent scale factors applied to each jet in the simulation within a range that reflects the systematic uncertainty in the measured tagging efficiency and mis-tag rates in data [71–73].
Other detector-related systematic uncertainties, such as those related to the ETmiss\documentclass[12pt]{minimal}
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\begin{document}$$E_{\mathrm{T}}^{\mathrm{miss}}$$\end{document} modelling, as well as lepton reconstruction efficiency, energy scale and energy resolution are found to have a small impact on the results.
Selection criteria used in the shape-fit to derive the model-dependent exclusion limits. The additional SR labelled as SR1ABh\documentclass[12pt]{minimal}
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\begin{document}$$\hbox {SR}_{1\mathrm{B}}^{h}$$\end{document} defined in Table 3
Systematic uncertainties are assigned to the FNP background estimation to account for different compositions (heavy flavour, light flavour or conversions) between the signal and control regions, as well as the contamination from prompt leptons in the regions used to measure the FNP probabilities.
The diboson background MC modelling uncertainties are estimated by varying the renormalisation, factorisation and resummation scales used to generate the samples [30]. For the tt¯Z\documentclass[12pt]{minimal}
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\begin{document}$$\hbox {MG}5\_{\textsc {a}}\hbox {MC}@\hbox {NLO}$$\end{document} interfaced to Pythia and Herwig 7.0.4 [85], while the uncertainties related to the choice of renormalisation and factorisation scales are assessed by varying the corresponding event generator parameters up and down by a factor of two around their nominal values [31]. For the tt¯\documentclass[12pt]{minimal}
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\begin{document}$$t\bar{t} $$\end{document} initial- and final-state radiation, renormalisation and factorisation scales are also considered [86].
The cross-sections used to normalise the MC samples are varied according to the uncertainty in the cross-section calculation, i.e. 6% for diboson, 12% for tt¯Z\documentclass[12pt]{minimal}
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Comparison of the observed and expected event yields in all the 3ℓ\documentclass[12pt]{minimal}
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\begin{document}$$t\bar{t} t\bar{t} $$\end{document} production. The lower panel shows the significance in each SR bin, computed as described in Ref. [88]
Results
The observed number of events and expected yields are shown in Tables 10 and 11 for each of the inclusive 3ℓ\documentclass[12pt]{minimal}
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\begin{document}$$\mathcal S$$\end{document} and jet multiplicity. The data agree with the SM background predictions and these results are interpreted as exclusion limits for several beyond-the-SM (BSM) scenarios.
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Model-dependent limits are also set in specific classes of SUSY models. For each signal hypothesis, the background fit is repeated taking into account the signal contamination in the CRs, which is found to be below 12% for signal models close to the existing exclusion limits [20]. Correlations of the uncertainties between the SM backgrounds and the signals are taken into account.
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\begin{document}$$\hbox {SR}_{2\mathrm{A}}^{\mathrm{Z}}$$\end{document}is used in the exclusion fits with no changes. The observed number of events and expected yields in all these bins are shown in Figs. 8 and 9.
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\begin{document}$$\pm 1 \sigma $$\end{document} uncertainty, respectively. The thick solid line is the observed limit for the central value of the signal cross-section. The expected and observed limits do not include the effect of the theoretical uncertainties in the signal cross-section. The dotted lines show the effect on the observed limit of varying the signal cross-section by ±1σ\documentclass[12pt]{minimal}
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Figure 10 shows the exclusion limits in the with simplified model with 50% branching ratios to each decay mode. These results are obtained from the statistical combination of the shape-fit bins of SR1AZ\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1$$\end{document} mass in this model by approximately 300 GeV [20].
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\begin{document}$$\tilde{t}_1$$\end{document} masses vary by at most 40 GeV depending on the branching ratios. However, for masses below 200 GeV the exclusion limits on t~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1$$\end{document} masses are up to 300 GeV better for models featuring only decays compared with models only considering the decays.
Figure 12 shows the exclusion limits in the t~2→Zt~1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_1 $$\end{document} and mass difference are also considered and the sensitivity is found to appreciably decrease only for values below 20 GeV. These results are obtained from the statistical combination of SR2AZ\documentclass[12pt]{minimal}
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\begin{document}$$\hbox {SR}_{2\mathrm{B}}^{\mathrm{Z}}$$\end{document} being most sensitive to small and large mass splittings between the t~2\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_2$$\end{document} up to 875 GeV are excluded at 95% CL for a mass of about 350 GeV and masses of approximately 520 (450) GeV are excluded for t~2\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_2$$\end{document} masses of 650 (800) GeV, extending beyond the previous limits on the mass from Ref. [89] by up to 160 GeV.
Conclusion
A search for direct top squark pair production in events with a leptonically decaying Z boson or a SM Higgs boson decaying into a b-quark pair is presented. The analysis uses 139 fb-1\documentclass[12pt]{minimal}
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\begin{document}$$\tilde{t}_2 \rightarrow Z\tilde{t}_1 $$\end{document} with decays. Compared with previous limits, these results extend the mass parameter space exclusion by up to 300 GeV in t~1\documentclass[12pt]{minimal}
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Acknowledgements
We thank CERN for the very successful operation of the LHC, as well as the support staff from our institutions without whom ATLAS could not be operated efficiently. We acknowledge the support of ANPCyT, Argentina; YerPhI, Armenia; ARC, Australia; BMWFW and FWF, Austria; ANAS, Azerbaijan; SSTC, Belarus; CNPq and FAPESP, Brazil; NSERC, NRC and CFI, Canada; CERN; CONICYT, Chile; CAS, MOST and NSFC, China; COLCIENCIAS, Colombia; MSMT CR, MPO CR and VSC CR, Czech Republic; DNRF and DNSRC, Denmark; IN2P3-CNRS and CEA-DRF/IRFU, France; SRNSFG, Georgia; BMBF, HGF and MPG, Germany; GSRT, Greece; RGC and Hong Kong SAR, China; ISF and Benoziyo Center, Israel; INFN, Italy; MEXT and JSPS, Japan; CNRST, Morocco; NWO, Netherlands; RCN, Norway; MNiSW and NCN, Poland; FCT, Portugal; MNE/IFA, Romania; MES of Russia and NRC KI, Russia Federation; JINR; MESTD, Serbia; MSSR, Slovakia; ARRS and MIZŠ, Slovenia; DST/NRF, South Africa; MINECO, Spain; SRC and Wallenberg Foundation, Sweden; SERI, SNSF and Cantons of Bern and Geneva, Switzerland; MOST, Taiwan; TAEK, Turkey; STFC, United Kingdom; DOE and NSF, United States of America. In addition, individual groups and members have received support from BCKDF, CANARIE, Compute Canada and CRC, Canada; ERC, ERDF, Horizon 2020, Marie Skłodowska-Curie Actions and COST, European Union; Investissements d’Avenir Labex, Investissements d’Avenir Idex and ANR, France; DFG and AvH Foundation, Germany; Herakleitos, Thales and Aristeia programmes co-financed by EU-ESF and the Greek NSRF, Greece; BSF-NSF and GIF, Israel; CERCA Programme Generalitat de Catalunya and PROMETEO Programme Generalitat Valenciana, Spain; Göran Gustafssons Stiftelse, Sweden; The Royal Society and Leverhulme Trust, United Kingdom. The crucial computing support from all WLCG partners is acknowledged gratefully, in particular from CERN, the ATLAS Tier-1 facilities at TRIUMF (Canada), NDGF (Denmark, Norway, Sweden), CC-IN2P3 (France), KIT/GridKA (Germany), INFN-CNAF (Italy), NL-T1 (Netherlands), PIC (Spain), ASGC (Taiwan), RAL (UK) and BNL (USA), the Tier-2 facilities worldwide and large non-WLCG resource providers. Major contributors of computing resources are listed in Ref. [90].
Data Availability Statement
This manuscript has no associated data or the data will not be deposited. [Authors’ comment: All ATLAS scientific output is published in journals, and preliminary results are made available in Conference Notes. All are openly available, without restriction on use by external parties beyond copyright law and the standard conditions agreed by CERN. Data associated with journal publications are also made available: tables and data from plots (e.g. cross section values, likelihood profiles, selection efficiencies, cross section limits, ...) are stored in appropriate repositories such as HEPDATA (http://hepdata.cedar.ac.uk/). ATLAS also strives to make additional material related to the paper available that allows a reinterpretation of the data in the context of new theoretical models. For example, an extended encapsulation of the analysis is often provided for measurements in the framework of RIVET (http://rivet.hepforge.org/).” This information is taken from the ATLAS Data Access Policy, which is a public document that can be downloaded from http://opendata.cern.ch/record/413 [opendata.cern.ch].]
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